A multivariate predictive model of academic performance and licensure outcomes among technical-vocational education graduates using demographic and learning condition indicators

Discover Education 2026 Open access

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Authors: Shaira Vita Mae G. Adviento, Christian Jeffrey G. Balintec, Chariza Mae B. Basamot, Eba Christie C. Rivera, Realyn Q. Salvador, Niña Theresa Grace S. Rabang, Kathleen C. Valendia, Daisy L. Franco, Christian John G. Tarampi, Nathaniel Dave B. Gatchalian, Shiella Mae G. Juan, Mark R. Limon
DOI: 10.1007/s44217-026-01707-3
Cited by: 1
References: 107

Abstract

Despite the rapid shift to online and hybrid modalities during the COVID-19 pandemic, limited empirical evidence exists on how instructional modes, demographic factors, and competency-based performance collectively shape licensure outcomes among teacher education graduates. This study addressed this gap by examining 150 Technical-Vocational and Livelihood Education graduates from a state university in Northern Philippines, analyzing their demographic profiles, course-level grades, and board examination results to develop a multivariate associative and exploratory predictive framework. Using MANOVA, the study found significant multivariate differences across instructional modes for both programs (BTLED Pillai’s Trace = 0.7788, p

Fields of Study & Subjects

Psychometric Methodologies and Testing Teacher Education and Assessments Occupational and Professional Licensing Regulation

Publication details

Journal / source
Discover Education
Publisher
Springer Science and Business Media LLC
Volume
5
Issue
1
Publication date
13 June 2026
Language
EN